incorporate data dependency in the clustering process. In this research we focus on clustering categorical sequences. The method … proposed here combines model-based and heuristic clustering. In the first step, the categorical sequences are transformed by an …, in the second step, using hierarchical clustering on the matrix of distances, the sequences can be clustered. This paper …

The topic of clustering has been widely studied in the field of Data Analysis, where it is defined as an unsupervised … process of grouping objects together based on notions of similarity. Clustering in the field of Multi-Criteria Decision Aid … clustering in MCDA using notions that are native to this field alone, and highlight the different structures which we may try to …

series model for each ATMs. For clustering, the succession of seven continuous daily withdrawal seasonality parameters of … better than the result of Andrawis, Atiya, and El-Shishiny (2011). This is due to clustering followed by a forecasting phase … without clustering. From a managerial perspective, the clusterwise cash demand forecast helps the bank’s top management to …